Principles of Genetic Epidemiology

Kirsten Ohm Kyvik

Genetic epidemiology

Genetic epidemiology deals with the etiology, distribution, and control of disease (epidemiology) in groups of relatives and with inherited causes of disease (genetics) in populations (adapted from Morton and Chung 1978)

Steps in genetic epidemiology

• Evidence for familial aggregation• Is familial aggregation due to genes or environment?• Specific genetic mechanisms Taking advantage of designs involving

Families Twins Adoptees and their families

Fundamentals

Definition of phenotype

Classification of phenotype

Natural history of phenotype

Adaptation of concept of causation

Family status changes risk profile Observations on family members not independent Boundary between cohort and case-control studies is

blurred

Multifactorial inheritance

Monogenic Quantitativ

Mød en forsker

TRESHOLD

MODEL

Family studies

Design of familiestudies

Identify probands – ”ascertainment probability”

Information on phenotype in relatives (1.degree, 2. degree etc.)

Compare groups of relatives

Compare with background population

Familial aggregation = genetic aetiology?

Against: Effect of:

Groups of relatives

Risk of siblings compared to risk in parent-offspring• RR(sib) = RR(par)

• RR(sib) >> RR(par

• RR(sib) and RR(par) small, but bigger than population risk

Expected risk pattern

0

10

20

30

40

50

60

70

MZ twins 1- degr 2- degr 3- degr

Ris

iko

%

Family risk

Parkinson’s disease in Iceland

(Sveinbjørnsdottir et al. NEJM, 2000)

Relatives Risk ratio(family vs population)

p

Sibling 6.3 <0.001

Children 3.0 0.001

Nephew/niece 2.4 <0.001

Cousin 2.4 0.1

Spouse 1.9 0.16

Genetic epidemiology of infantile hypertrophic pyloric

stenosis

The IHPS register

• Funen based• Cases from 1950 to 2004• A total of 892 cases, 870 identified in CPR• Questionnaire send to all cases• Reply from 65%

Smoothed prevalence

0

1

2

3

4

5

6

7

1950 1960 1970 1980 1990 2000Year

All BoysGirls

Recurrence risk in relatives

Recurrence risk % (95% Confidence Interval)

Group Female Male All

Population 0.11 (0.06-0.15)

0.43 (0.40-0.46)

0.27 (0.24-0.30)

1.degree 5.7 (3.9-9.5) 4.4 (3.4-6.1) 4.8 (4.1-7.0)

Parent 4.5 (1.4-7.4) 3.9 (2.4-5.7) 4.0 (2.9-6.2)

Offspring 4.5 (0.14-5.3)

4.5 (0.10-8.3)

4.5 (0.24-8.3)

Siblings 11.4 (4.0-17.5)

5.1 (3.0-10.8)

6.6 (4.7-9.8)

2. degree

Grandparents

0.76 (-0.13-1.5)

0.51 (0.10-1.1)

0.57 (0.20-1.0)

Twin studies

Aims

• What is the risk/recurrence risk in twins• Is a phenotype genetically determined• Aetiological models• Size of genetic variation / heritability• Genes, markers, chromosomal regions• Environmental determinants

DESIGNS

Classical twin study

Classical twin study with separated MZ twins

Twin family studies

Twin-control studies

Classical twin study

MZ pairs:

DZ pairs:

DESIGNS

Classical twin study

Classical twin study with separated MZ twins

Twin family studies

Twin-control studies

Is a phenotype genetically determined?

• Categorical data

• Continous data

Types of concordance

Pairwise: Probability that both in a pair is affected:

Casewise/probandwise: Probability that a twin is diseased given that the twin partner is diseased:

Probandwise concordance Estimate of the casewise probability by the proband method.

2C1 + C2

2C1 + C2 + D -----------------

Concordance

CMZ = CDZ

CMZ > CDZ

CMZ <1.0 (100%)

Solutions to problems with age at diagnosis

Survival analysis

Actuarial/Kaplan Meier methodology

Frailty models

Newer models

Others?

Correction methods

Concordance type 1 diabetes

Zygosity Pairs Concordance (probands) Pairwise* Probandwise Cumulated

Conc Disc

MZ 10(18) 16 0.38 0.53 0.70

[0.20-0.59] [0.33-0.73] [0.45-0.95)

DZ 4 (8) 65 0.06 0.11 0.13

[0.02-0.14] [0.05-0.21] [0.04-0.21]

( ) Number of probands; [ ] 95% confidence limits.

* Chi21d.f. = 10.93, p < 0.001

Cumulative concordance type 1 diabetes

Interpretable as cumulative risk from birth

%0-100

Age 0-40

MZ0.70

DZ0.13

Correlations

Twin-twin correlations

rMZ = rDZ

rMZ > rDZ

rMZ < 1.0 (100%)

lnT

SH

in T

win

2

lnTSH in Twin 1-2 -1 0 1 2

-2

-1

0

1

2

lnT

SH

in T

win

2

lnTSH in Twin 1-2 -1 0 1 2

-2

-1

0

1

2rMZ=0.64 (CI 0.56-0.70) rDZ=0.29 (CI 0.18-0.39)

MZ n=284 pairs DZ n=285 pairs

p<0.00005

INTRACLASS CORRELATIONSlnTSH (Pia Skov Hansen)

0,6625 0,6358

0,2915

0,1814

0,3577

0,6373

0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9

1

All Male Female

rMZ

rDZ

INTRACLASS CORRELATIONSlnTSH

Aetiological components

Additive genetic variance

Dominant genetic variance/epistasis

Common environmental variance

Unique environmental variance

Genotype Group

Model AA Aa aa

A is Dominant

A is Recessive

A is Co-Dominant

Inheritance Models in Single Gene Trait

Population MeanModel -x 0 +x

A is Completely Dominant

aa

AAAa

A is Partially Dominant

aa Aa AA

A is Not Dominant

aa Aa AA

Inheritance Models in Quantitative Trait

Heritability

V (total) = VG + VE

V (total) = VA + VD + VI + VC + VE

h2narrow = VA/VA + VD + VI + VC + VE

h2broad = VA + VD + VI/VA + VD + VI + VC + VE

Heritability

Function of population, NOT a constant Does not apply to individuals Biased if mean and variance not the same in MZ

and DZ Greater MZ covariance will inflate h2

Correlations and aetiological models

rMZ < 1

rMZ = rDZ = 0

rMZ = rDZ > 0

rMZ = 2rDZ > 0

rMZ > 2rDZ

rMZ < 2rDZ

Aetiological models and genetic variation

Variance analysis Regression analysis Structural equation modelling

Path model for twin analysis

Pleiotrophy

UniqueEnvironmental

effect0.36

Geneticeffect0.64

The genetic effects account for 64% of the variation

RESULTS TSH-LEVEL

BMI Waist Gluc120 Ins0 SBP DBP HDL TG

BMI0.86 (0.01

)

-0.13 (0.06)

0.48 (0.04)

0.29(0.04)

0.27(0.04)

-0.18(0.05)

0.20(0.06)

Waist 0.85 (0.01)

-0.16 (0.06)

0.51 (0.05)

0.30(0.05)

0.26(0.05)

-0.19(0.06)

0.26(0.06)

Gluc120

0.02

(0.03)

0.03 (0.03

)

0.09 (0.08)

0.12(0.07)

0.11(0.07)

-0.02(0.08)

0.23(0.08)

Ins00.46

(0.02)

0.46

(0.02)

0.13 (0.03)

0.31(0.06)

0.29(0.06)

-0.17(0.07)

0.31(0.07)

SBP 0.28(0.03)

0.26(0.03

)

0.14(0.03)

0.23(0.03)

0.71(0.03)

-0.09(0.06)

0.28(0.06)

DBP 0.26(0.03)

0.23(0.03

)

0.13(0.03)

0.23(0.03)

0.69(0.02)

-0.01(0.06)

0.27(0.06)

HDL -0.17(0.03)

-0.19(0.03

)

-0.04(0.03)

-0.14(0.03)

-0.01(0.03)

-0.03(0.03)

-0.24(0.07)

TG 0.22(0.03)

0.27(0.03

)

0.20(0.03)

0.35(0.02)

0.20(0.03)

0.20(0.03)

-0.22(0.03)

Multivariate ACE Model

Important assumptions

• Biology of twinning • ”True” zygosity • Equal environment assumption

• true or not true? • Generalisability

Adoption studies

Adoption design

Adoptees are expected to

Early death in adopteesCause of death Parent dead < 50

yrsParent dead < 70 yrs

NaturalBioAdo

1.98*0.96

1.490.8

InfectionBioAdo

5.81*0.73

5*1

VasculærBio Ado

4.52*3.02

1.921.5

CancerBioAdo

1.195.16*

0.871.49

Assumptions and problems

Early adoption Non-familial adoption Comparable environment in biological and adoptive

family Contact to biological family Intra-uterine environment Transcultural adoptions

Comparison of correlations

Correlation

Twin studiesMZDZMZA

0.70.360.7

Family studiesPOSib

0.270.25

Adoption studiesBioAdo

0.170.1

Comparison heritabilityHeritability

Twin studiesMZA

50-90%60-70%

Family studies 20-80%

Adoption studies 20-60%